Cloud Machine Learning Engineer Job Description [Updated for 2025]

In the era of big data, the role of Cloud Machine Learning Engineers has taken center stage.

As technology continues to evolve, the demand for proficient individuals who can design, develop, and secure our cloud-based machine learning systems has grown exponentially.

But let’s delve deeper: What’s truly expected from a Cloud Machine Learning Engineer?

Whether you are:

• A job aspirant trying to understand the nuances of this role,
• A hiring manager detailing the perfect candidate,
• Or simply fascinated by the intricacies of cloud-based machine learning,

You’ve come to the right place.

Today, we present a customizable Cloud Machine Learning Engineer job description template, designed for effortless posting on job boards or career websites.

Let’s dive right in.

Cloud Machine Learning Engineer Duties and Responsibilities

Cloud Machine Learning Engineers use their strong understanding of machine learning algorithms and cloud platforms to build and implement machine learning models in cloud environments.

Their main goal is to create applications that can make predictions and improve decision making based on data analysis.

The duties and responsibilities of a Cloud Machine Learning Engineer include:

• Designing, developing and maintaining machine learning models in cloud environments
• Using machine learning and data mining techniques to solve complex problems and improve business outcomes
• Collaborating with data engineers to build data and model pipelines
• Applying cloud computing skills to deploy models in a scalable environment
• Working with cross-functional teams to understand business needs and provide AI solutions
• Monitoring and optimizing performance of deployed models
• Staying current with the latest machine learning and cloud technologies and trends
• Documenting and communicating technical processes, model details, and performance metrics
• Addressing issues that arise during the model development and deployment process
• Ensuring strict compliance with data privacy and protection regulations

 

Cloud Machine Learning Engineer Job Description Template

Job Brief

We are looking for a talented Cloud Machine Learning Engineer to join our team.

Your primary responsibilities include designing, building, and deploying Machine Learning models on our cloud platforms.

You should be able to understand business requirements, build Machine Learning models, and deploy them on cloud platforms like AWS, Google Cloud, or Microsoft Azure.

The ideal candidate should have a solid understanding of Machine Learning concepts, cloud platforms, and software development principles.

 

Responsibilities

• Design, develop, and implement Machine Learning models.
• Work with large and complex data sets to evaluate, recommend, and support the implementation of business strategies
• Work with stakeholders to identify opportunities for leveraging data to drive business solutions
• Develop cloud-based data storage and data pipelines for Machine Learning
• Work with cross-functional teams to ensure models can be implemented as part of a delivered solution replicable across many clients
• Deploy Machine Learning models on cloud platforms (AWS, Google Cloud, Microsoft Azure)
• Monitor performance and advise on necessary infrastructure changes
• Define and enforce coding standards, development processes, and system performance standards

 

Qualifications

• Proven work experience as a Machine Learning Engineer or similar role
• Understanding of data structures, data modeling and software architecture
• Deep knowledge of math, probability, statistics and algorithms
• Experience with machine learning frameworks (like Keras, TensorFlow or PyTorch) and libraries (like scikit-learn)
• Proficiency in Python or Java
• Experience with cloud services (AWS, Google Cloud, Microsoft Azure)
• Excellent communication skills
• Ability to work in a team
• Outstanding analytical and problem-solving skills
• MSc in Computer Science, Mathematics or similar field; Ph.D. degree is a plus

 

Benefits

• 401(k)
• Health insurance
• Dental insurance
• Retirement plan
• Paid time off
• Professional development opportunities

 

Additional Information

• Job Title: Cloud Machine Learning Engineer
• Work Environment: Office setting with options for remote work. Some travel may be required for team meetings or client consultations.
• Reporting Structure: Reports to the Lead Data Scientist or Machine Learning Manager.
• Salary: Salary is based upon candidate experience and qualifications, as well as market and business considerations.
• Pay Range: $140,000 minimum to $240,000 maximum
• Location: [City, State] (specify the location or indicate if remote)
• Employment Type: Full-time
• Equal Opportunity Statement: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
• Application Instructions: Please submit your resume and a cover letter outlining your qualifications and experience to [email address or application portal].

 

What Does a Cloud Machine Learning Engineer Do?

Cloud Machine Learning Engineers are specialized software engineers who focus on designing, developing, and deploying machine learning models on cloud platforms.

They are responsible for the end-to-end process, which includes data collection and preprocessing, model development, training, tuning, and deployment.

This often involves working with large and complex data sets, making sure they are clean, structured, and ready for use.

These engineers use a variety of machine learning techniques and algorithms, ranging from supervised learning methods such as regression and classification, to unsupervised learning methods such as clustering.

They work extensively with cloud platforms like Google Cloud, AWS, and Microsoft Azure, using their machine learning services and infrastructure to build, train, and deploy models.

They manage and optimize these models to ensure their efficient and effective operation, often automating this process through the use of scripts and other tools.

Cloud Machine Learning Engineers also work closely with data scientists and other stakeholders to understand their requirements and translate them into machine learning solutions.

They also need to keep up to date with the latest developments in the field to ensure they are using the most effective techniques and tools.

In addition, these engineers are also responsible for creating APIs to allow other applications to interact with the machine learning models, and ensure the security and privacy of data processed and stored in the cloud.

They also monitor the performance of models and make necessary adjustments based on feedback or changing requirements.

 

Cloud Machine Learning Engineer Qualifications and Skills

Cloud Machine Learning Engineers work with a variety of technical skills, problem-solving abilities, and industry knowledge to develop, deploy and maintain machine learning models on the cloud.

These include:

• Strong understanding of machine learning algorithms, data structures, and performance optimization techniques.
• Experience in cloud platforms such as AWS, GCP, or Azure, and familiar with tools and services related to machine learning and data processing on the cloud.
• Proficient in programming languages such as Python, Java, or R, and tools like TensorFlow, PyTorch, or Keras for developing machine learning models.
• Ability to translate complex business problems into machine learning projects, and then develop and deploy the models using cloud infrastructure.
• Exceptional communication skills to effectively collaborate with data scientists, business analysts, and other stakeholders, and to explain complex machine learning concepts to non-technical team members.
• Strong problem-solving and analytical skills to diagnose and quickly resolve issues that may arise during the development, deployment, and maintenance of machine learning models.
• Attention to detail and organizational skills to manage multiple projects simultaneously, and to ensure the accuracy and reliability of machine learning models.
• Understanding of data privacy regulations and ethical considerations in machine learning and AI.

 

Cloud Machine Learning Engineer Experience Requirements

Cloud Machine Learning Engineers usually require a minimum of 2 to 3 years of direct experience with machine learning, data mining, or statistical modeling.

This experience can be obtained through a combination of work, research, projects, or internships.

They often need a solid understanding of cloud computing technologies and platforms.

Experience with specific cloud services, such as AWS, Google Cloud, or Microsoft Azure, is often preferred.

Candidates with around 5 years of experience in data analysis and software engineering roles are typically expected to have developed their skills in programming languages like Python, Java, or Scala and tools such as TensorFlow, PyTorch, or Keras.

Those with over 7 years of experience may have had exposure to more advanced aspects of machine learning engineering such as deep learning, neural networks, and natural language processing.

They may also have leadership experience and could be ready for managerial or team-lead roles in Machine Learning engineering teams.

Additional qualifications such as certifications in cloud services or machine learning can enhance a candidate’s suitability for the role.

Examples include Google’s Professional Machine Learning Engineer Certification, AWS Certified Machine Learning – Specialty, or Microsoft Certified: Azure AI Engineer Associate.

 

Cloud Machine Learning Engineer Education and Training Requirements

Cloud Machine Learning Engineers typically have a bachelor’s degree in computer science, data science, artificial intelligence, or a related field.

Proficiency in programming languages like Python, Java, or R is a must.

They are also expected to have deep knowledge of machine learning algorithms and cloud computing platforms, such as AWS, Google Cloud, or Azure.

Many positions require a master’s degree in a field like computer science, machine learning, or data science.

This is especially true for roles that involve creating complex machine learning models or managing large scale data.

Several organizations and platforms offer certifications in machine learning and cloud computing.

These certifications can enhance a candidate’s skill set and make them more appealing to employers.

Certifications like AWS Certified Machine Learning Specialist or Google Cloud Certified – Professional Machine Learning Engineer are highly sought after in the industry.

Moreover, a candidate’s understanding of data structures and algorithms, statistics, and deep learning frameworks like TensorFlow or PyTorch can further improve their employability.

Continuing education and staying updated with the latest advancements in cloud technologies, machine learning algorithms, and data science tools is crucial for growth and development in this field.

 

Cloud Machine Learning Engineer Salary Expectations

A Cloud Machine Learning Engineer earns an average salary of $114,121 (USD) per year.

The actual salary can vary based on factors such as the engineer’s years of experience, the complexity of the projects they handle, their educational background, and the city or country where they work.

Other factors that could influence the salary include the size of the employing company and the specific industry in which they operate.

 

Cloud Machine Learning Engineer Job Description FAQs

What skills does a Cloud Machine Learning Engineer need?

A Cloud Machine Learning Engineer should have a robust understanding of machine learning concepts and techniques, deep knowledge of cloud computing platforms like Google Cloud, AWS, or Azure, and strong programming skills in languages like Python or R.

They should also have proficiency in data modeling, evaluation, and using machine learning libraries and frameworks.

Strong problem-solving abilities, analytical thinking, and excellent communication skills are essential too.

 

Do Cloud Machine Learning Engineers need a degree?

Yes, most Cloud Machine Learning Engineer positions require at least a bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.

However, due to the specialized nature of the work, many employers prefer candidates with a master’s degree or Ph.D. in these fields.

Practical experience with cloud platforms and machine learning algorithms is also highly valued.

 

What should you look for in a Cloud Machine Learning Engineer resume?

The resume of a Cloud Machine Learning Engineer should detail their educational qualifications, especially in fields like computer science or data science.

It should also mention their experience with machine learning algorithms and cloud platforms.

Certifications in cloud technologies like AWS, Google Cloud, or Azure are a plus.

Any projects or work experience illustrating their skills in developing and implementing machine learning models in a cloud environment will also be useful.

 

What qualities make a good Cloud Machine Learning Engineer?

A good Cloud Machine Learning Engineer is detail-oriented and capable of analytical thinking.

They are continually learning and staying up-to-date with the latest developments in machine learning and cloud technologies.

They should be able to work effectively in a team, communicate complex ideas clearly, and problem-solve under pressure.

 

Is it difficult to hire Cloud Machine Learning Engineers?

Yes, hiring a Cloud Machine Learning Engineer can be challenging due to the specialized and highly technical nature of the role.

There is high demand for these professionals, and the pool of qualified candidates is limited.

Therefore, it’s important to offer competitive salaries, opportunities for professional growth, and a work environment that encourages innovation and learning.

 

Conclusion

And there we have it.

Today, we’ve shed light on the intriguing world of a Cloud Machine Learning Engineer.

Surprise, surprise?

It’s not just about creating algorithms.

It’s about shaping the future of data-driven technology, one machine learning model at a time.

Armed with our handy Cloud Machine Learning Engineer job description template and real-world examples, you’re ready to embark on this journey.

But why hold back?

Immerse yourself further with our job description generator. It’s your ultimate guide to drafting pinpoint-accurate job listings or refining your resume to absolute precision.

Keep this in mind:

Every machine learning model contributes to the grand scheme of things.

Let’s create this future. Together.

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